Method and apparatus for deblocking an image

ABSTRACT

Different implementations are described, particularly implementations for video encoding and decoding are presented including a method for deblocking an image. According to an implementation, in a method for deblocking an image, at least one boundary is determined between a first block of samples and a second block of samples: a boundary strength is determined according to at least one of a prediction mode of the first block and a prediction mode of the second block; and samples of the first and second blocks neighboring the at least one boundary are filtered according to the boundary strength. Advantageously, in case the prediction mode of the first block is a weighted prediction mode, the boundary strength further depends on the relative weight of samples used in predicting the first block of samples according to the weighted prediction mode of the first block and reciprocally for the second block.

TECHNICAL FIELD

At least one of the present embodiments generally relates to, e.g., amethod or an apparatus for video encoding or decoding, and moreparticularly, to a method or an apparatus for deblocking an image.

BACKGROUND

The technical field of the one or more implementations is generallyrelated to video compression. At least some embodiments relate toimproving compression efficiency compared to existing video compressionsystems such as HEVC (HEVC refers to High Efficiency Video Coding, alsoknown as H.265 and MPEG-H Part 2 described in “ITU-T H.265Telecommunication standardization sector of ITU (10/2014), series H:audiovisual and multimedia systems, infrastructure of audiovisualservices—coding of moving video, High efficiency video coding,Recommendation ITU-T H.265”), or compared to under development videocompression systems such as VVC (Versatile Video Coding, a new standardbeing developed by JVET, the Joint Video Experts Team).

To achieve high compression efficiency, image and video coding schemesusually employ partitioning of an image, prediction, including motionvector prediction, and transform to leverage spatial and temporalredundancy in the video content. Generally, intra or inter prediction isused to exploit the intra or inter frame correlation, then thedifferences between the original image and the predicted image, oftendenoted as prediction errors or prediction residuals, are transformedinto frequency-domain coefficients, the coefficients are quantized, andentropy coded. To reconstruct the video, the compressed data are decodedby inverse processes corresponding to the entropy decoding, inversequantization, inverse transform, and prediction.

In codecs such as HEVC or VVC, the deblocking filter DBF is appliedafter the pictures have been reconstructed and aims at reducing blockingartefacts by smoothing the sample values near the block edges. Thedeblocking filter is defined using traditional square or rectangularblock partitioning shapes of size at least equal to 4 samples in Lumasamples. Then, the selection of the motion vectors, reference indexesand the reference deblocking samples to be used for the determination ofthe deblocking fitter strength is performed. For instance, Norkin et aldescribe principles of deblocking in “HEVC Deblocking Filter” (IEEETransactions on Circuits and Systems for Video Technology, vol. 22 No.12. December 2012).

In recent video codec approach, new coding (prediction) modes areconsidered where the prediction samples are built using combination ofnon-square or non-rectangular blocks (e.g. Triangle) and/or thecombination of unequal (e.g. Generalized bi-prediction GBi also referredto as Bi-prediction with CU level Weights BCW) and/or spatially variableweighting (e.g. Multi-Hypothesis or Combined Inter merge IntraPrediction CIIP). It is thus desirable to adapt the deblocking filterprocess to such coding mode to still efficiently reduce blockingartefacts.

SUMMARY

The purpose of the invention is to overcome at least one of thedisadvantages of the prior art. For this purpose, according to a generalaspect of at least one embodiment, a method for deblocking a part of animage is presented. The method comprises determining at least oneboundary between a first block of samples and a second block of samples,the first block and second block belonging to the part of an image tofilter: determining a boundary strength according to at least one of aprediction mode of the first block and a prediction mode of the secondblock; and filtering the at least one boundary according to the boundarystrength, i.e. filtering samples of the first and second blockneighboring the at least one boundary. In case the prediction mode ofthe first block is a weighted prediction mode, the boundary strengthfurther depends on the relative weight of samples used in predicting thefirst block of samples according to the weighted prediction mode of thefirst block. Naturally, the same applies for the second block withoutdistinction: In case the prediction mode of the second block is aweighted prediction mode, the boundary strength further depends on therelative weight of samples used in predicting the second block ofsamples according to the weighted prediction mode of the second block. Aweighted prediction mode is a coding mode wherein a prediction isobtained from a weighted combination of a first predictor determinedusing a first prediction mode and of a second predictor determined usinga second prediction mode.

According to another general aspect of at least one embodiment, a methodfor encoding a block in an image encoding is presented. The methodcomprises reconstructing an image part; and filtering the reconstructedimage part according to any one of the embodiments of the deblockingmethod.

According to another general aspect of at least one embodiment, a methodfor decoding a block of an image is presented comprising decoding a partof an image part and filtering the decoded image part according to anyone of the embodiments of the deblocking method.

According to another general aspect of at least one embodiment, anapparatus for video encoding is presented comprising means forimplementing any one of the embodiments of the encoding method.

According to another general aspect of at least one embodiment, anapparatus for video decoding is presented comprising means forimplementing any one of the embodiments of the decoding method.

According to another general aspect of at least one embodiment, anapparatus for video encoding is provided comprising one or moreprocessors, and at least one memory. The one or more processors isconfigured to implement to any one of the embodiments of the encodingmethod.

According to another general aspect of at least one embodiment, anapparatus for video decoding is provided comprising one or moreprocessors and at least one memory. The one or more processors isconfigured to implement to any one of the embodiments of the decodingmethod.

According to another general aspect of at least one embodiment, aweighted prediction mode is one of a Generalized Bi-prediction, aBi-prediction with Coding Units level Weights, a Multi-Hypothesisprediction combining intra and inter predicted samples or combininginter and inter predicted samples, a Combined Inter merge IntraPrediction combining inter merge and intra predicted samples, aGeometric prediction combining inter predicted samples according to ageometric partition of a block, a Triangle prediction combining interpredicted samples along a diagonal edge of a block.

According to another general aspect of at least one embodiment,predicting the first block of samples according to the weightedprediction mode of the first block comprises predicting a sample of thefirst block as weighted combination of a first predictor determinedusing a first prediction mode and of a second predictor determined usinga second prediction mode, and the sample of the first block isconsidered as using the first prediction mode for determining theboundary strength in case the weight of a first predictor is above alevel.

According to another general aspect of at least one embodiment, thefirst prediction mode is one intra prediction mode and the sample of thefirst block is considered as using intra prediction mode for determiningthe boundary strength. In a variant, the first prediction mode is intraplanar prediction mode and the sample of the first block is consideredas using intra prediction mode for determining the boundary strength. Ina variant, the boundary strength is set to strong in case of intraprediction mode.

According to another general aspect of at least one embodiment, thefirst prediction mode is one inter prediction mode and the sample of thefirst block is considered as using inter prediction mode for determiningthe boundary strength. In a variant, the first prediction mode is aninter bi-directional prediction mode and the sample of the first blockis considered as using inter bi-directional prediction mode fordetermining the boundary strength. In another variant, the firstprediction mode is an inter unidirectional prediction mode and thesample of the first block is considered as using inter unidirectionalprediction mode for determining the boundary strength.

According to another general aspect of at least one embodiment, thelevel in the determination of BS is set to zero.

According to another general aspect of at least one embodiment, theboundary strength is determined for a group of samples of the blocksharing a same relative weight, the group of samples comprising at leastone sample, 4×4 samples up to all samples of the block.

According to another general aspect of at least one embodiment, anon-transitory computer readable medium is presented containing datacontent generated according to the method or the apparatus of any of thepreceding descriptions.

According to another general aspect of at least one embodiment, a signalor a bitstream is provided comprising video data generated according tothe method or the apparatus of any of the preceding descriptions.

One or more of the present embodiments also provide a computer readablestorage medium having stored thereon instructions for deblocking,encoding or decoding video data according to any of the methodsdescribed above. The present embodiments also provide a computerreadable storage medium having stored thereon a bitstream generatedaccording to the methods described above. The present embodiments alsoprovide a method and apparatus for transmitting the bitstream generatedaccording to the methods described above. The present embodiments alsoprovide a computer program product including instructions for performingany of the methods described.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 a illustrates of an exemplary flowchart of the in-looppost-filtering stage in a decoder architecture.

FIG. 1 b illustrates of an example of a decoded image before deblockingfilter (left) and after (right).

FIG. 2 illustrates an example of block boundary samples with a blockingartefact (left) between 2 blocks of samples (right).

FIG. 3 illustrates an exemplary flowchart of the determination of theBoundary Strength (BS) parameter in a deblocking filter method accordingto a particular embodiment.

FIG. 4 illustrates an exemplary flowchart of the determination of theFilter Strength (FS) in a deblocking filter method according to aparticular embodiment.

FIG. 5 illustrates of an example of a multi-hypothesis prediction incase of inter and intra modes combination.

FIG. 6 illustrates of examples of a non-rectangular partitioning (top)and an example of overlap block motion compensation diagonal weightingassociated to a triangle partitioning (bottom).

FIG. 7 illustrates of an example of a triangle logical partitioning(left) and a blending map (right) according to a particular embodiment.

FIG. 8 illustrates an example of a method for deblocking a part of animage according to a general aspect of at least one embodiment.

FIG. 9 illustrates a flowchart of a determination of the BoundaryStrength in a deblocking filter method according to a particularembodiment.

FIG. 10 illustrates 2 flowcharts of the storing of CU parameters used inthe determination of the Boundary Strength (BS) parameter in adeblocking filter method according to a particular embodiment.

FIG. 11 illustrates a block diagram of an embodiment of video encoder inwhich various aspects of the embodiments may be implemented.

FIG. 12 illustrates a block diagram of an embodiment of video decoder inwhich various aspects of the embodiments may be implemented.

FIG. 13 illustrates a block diagram of an example apparatus in whichvarious aspects of the embodiments may be implemented.

DETAILED DESCRIPTION

It is to be understood that the figures and descriptions have beensimplified to illustrate elements that are relevant for a clearunderstanding of the present principles, while eliminating, for purposesof clarity, many other elements found in typical encoding and/ordecoding devices. It will be understood that, although the terms firstand second may be used herein to describe various elements, theseelements should not be limited by these terms. These terms are only usedto distinguish one element from another.

The various embodiments are described with respect to theencoding/decoding of an image.

They may be applied to encode/decode a part of image, such as a slice ora tile, a tile group or a whole sequence of images.

Various methods are described above, and each of the methods comprisesone or more steps or actions for achieving the described method. Unlessa specific order of steps or actions is required for proper operation ofthe method, the order and/or use of specific steps and/or actions may bemodified or combined.

At least some embodiments relate to adapting the deblocking fitter DBFin the case of the blocks have been encoded with one of the followingthree prediction modes:

-   -   Generalized Bi-prediction (GBi) or Bi-prediction with CU level        Weights (BCW),    -   Multi-Hypothesis (MH) or a simplified version called Combined        Inter merge Intra Prediction CIIP,    -   Geometric or Triangle mode.

Advantageously, the present principles increase the efficiency of priorart methods by preserving DBF intent and efficiency in a block-basedvideo codec where non-square or non-rectangular blocks are supported,and/or the combination of blocks with variable weighting are supported.

In the following, a generic embodiment for a deblocking method isdisclosed and at least 3 prediction modes for which the deblockingfilter is adapted are disclosed. Then, several embodiments of a modifieddeblocking filter are disclosed

Generic Embodiment for a Deblocking Method and Exemplary PredictionModes for Which Deblocking Filter is Adapted

Traditional video coding scheme includes in-loop filtering processes forimproving the quality of the reconstructed images. In-loop filtering cancomprise several filtering processes such as Deblocking Filtering (DBF),Sample Adaptive Offset (SAO) filtering as in HEVC, and/or Adaptive LoopFiltering ALF such as Wiener filters. These filters can be appliedsuccessively in this order or in a different order. FIG. 1 a illustratesof an exemplary flowchart of the in-loop post-filtering stage in adecoder architecture. Typically, the deblocking filter (DBF) is one ofthe coding artefacts reduction post-filters (20) and is applied afterthe block samples have been reconstructed (10). The post-filteredpictures can be displayed and are possibly stored in the decoded picturebuffer (30) to be used for building the motion compensated prediction.

Advantageously, the same in-loop post filtering is also used in theencoder for reconstructed images used in temporal prediction.

FIG. 1 b illustrates of an example of a decoded image before deblockingfilter (left) and after deblocking filter (right). The deblocking filteris applied after the pictures have been reconstructed (10). It aims atreducing blocking artefacts by smoothing the sample values near theblock edges as illustrated on FIG. 1 b.

FIG. 2 illustrates an example of block boundary samples with a blockingartefact (left) between 2 blocks P and Q of samples (right). The samplesP={p0,p1,p2,p3} and Q={q0,q1,q2,q3} belong to two adjacent blocks P andQ. The samples belongs to square 4×4 blocks P and Q as shown on theright of FIG. 2 where the second index i in samplesP={p0_(i),p1_(i),p2_(i),p3_(i)} is the line index in the 4×4 block. Ingeneral, the artefact visibility is proportional to the relativedifference between samples values P and Q as shown on the left of FIG. 2. That is why, the DBF filtering performs sample smoothing S across theblock edges. The smoothing/filtering function S parameters are:

-   -   Boundary strength (BS)={0-weak, 1-normal or 2-strong}    -   Sample values of the blocks P, Q

The determination of DBF parameters for a square block is carried-outfor each set of line (or column) samples on each side of a vertical(resp, horizontal) boundary {p3_(i), p2_(i), p1_(i), p0_(i), q0_(i),q1_(i), q2_(i), q3_(i)}.

FIG. 3 illustrates an exemplary flowchart of the determination 300 ofthe Boundary Strength (BS) parameter in a deblocking filter methodaccording to a particular embodiment. Let's denote {MVi_(x),ref-i_(x)}the motion vector MV value and reference index for the list *i* for theblock X (X=P or Q). By convention, if the block X is uni-directionallypredicted with list-0, then {MV0 _(x) is set to zero and ref-0_(x) isset to “−1”}. Respectively, if the block X is uni-directionallypredicted with list-1, then {MV1 _(x) is set to zero and ref-1_(x) isset to “−1”}.

The determination 300 of Boundary Strength BS depends of several blockparameters and turns out in successive checks. For example, the checksare:

-   -   (305): P or Q is intra (else considered as inter). In case of        the check results in no, then both P and Q block are inter        predicted, with associated motion vectors and reference index        pictures, and further check are processed to determine BS. In        case P or Q is intra, the check results in yes, the BS is set to        2-strong.    -   (310): P or Q has non-zero coefficients and the boundary is        transform boundary.    -   (320): P and Q have different reference indexes. Thus according        to a non-limiting example, if P is bi-predicted ({MV0        _(P),ref-0_(P)}, {MV1 _(P),ref-1_(P)}) and Q is uni-directional        predicted {MV0 _(Q), ref-0_(Q)}, then check if:

ref-0_(P)≠ref-0_(Q) and ref-1_(P)≠ref-0_(Q)  (check.1)

-   -   (330): P and Q have different number of reference        (uni-directional or bi-prediction). In a variant, (330) is not        present and in uni-dir, the MV value of the missing reference is        inferred to be zero.    -   (340): P and Q motion vectors with same reference have different        values. Thus according to a non-limiting example, if P is        bi-predicted ({MV0 _(P),ref-0_(P)}, {MV1 _(P),ref-1_(P)}) and Q        is uni-directional predicted {MV0 _(Q),ref-0_(Q)}, then check        if:

if ref-0_(P)=ref-0_(Q) and |MV0_(P)−MV0_(Q)|>threshold

or if ref-1_(P)=ref-0_(Q) and |MV1_(P)−MV0_(Q)|>threshold  (check. 2)

-   -   The skilled in the art will non ambiguously derive the checks in        case of 2 bi-predicted blocks or 2 uni-predicted blocks from        above equations of (check. 2).

In case of block of Luma samples, only block boundaries with BS equal to1 or 2 are filtered. In case of block of Chrome samples, only blockboundaries with BS equal to 2 are filtered.

FIG. 4 illustrates an exemplary flowchart of the determination of theFilter Strength in a deblocking filter method according to a particularembodiment. Thus, independently to the way BS is determined (300), anadditional test (415) determines whether filtering applies or not, basedon a set of conditions involving combination of absolute differences ofweighted sample values compared to a pre-determined threshold β:

|p2₀−2p1₀ +p0₀ |+|p2₃−2p1₃ +p0₃ |+|q2₀−2q1₀ +q0₀ |+|q2₃−2q1₃ +q0₃|>β  (eq.1)

If the filter applies, the filtering process (430) modifies one or moreof the P,Q samples in each side of the boundary of FIG. 2 depending onthe samples values (410 accessing sample values). The strength of thefiltering process (normal or strong) is determined (420) for each line(resp, column) of samples on each side of the boundary, based on a setof conditions involving combination of absolute differences of weightedsample values compared to pre-determined thresholds. Some thresholds arefunction of the quantization parameter (QP) (440).

The number of samples modified by (430) on each side of the blockboundary depends on the filter strength. The stronger filter strengthaffects more pixels on each side of the block boundary.

At least 3 new prediction modes involving weighted prediction withunequal or spatially variable weights in the block and for which thedeblocking filter is adapted are now disclosed.

A First Prediction Mode for which Deblocking Filter is Adapted:Generalized Bi-Prediction (GBI)

In case of bi-prediction, two prediction blocks are computed andcombined with weighted sum to obtain the final block prediction asfollows:

P _(GBI)=(((1<<gs)−gw ₁)·P ₀ +gw ₁ ·P ₁)>>gs  (eq.2)

In the WC reference software (VTM), the weights to use are coded per CUwith a “gbi-index” which values are depicted in Table 1.

TABLE 1 Binarization of GBi index and associated weights. Binarizationof GBi Index Weight value of w₁ gw₁ gs (shift) GBi Index 0 −1/4  −1 20000 1 3/8 3 3 001 2 1/2 1 1 1 3 5/8 5 3 01 4 5/4 5 2 0001

Hereafter, the weight pair {½; ½} will be called the default weights.

A Second Prediction Mode for Which Deblocking Filter is Adapted:Multi-Hypothesis

The general concept of Multi Hypothesis MH is to combine an interprediction P0 (which can be uni-directional or bi-predicted) performedin merge mode (where a list of merge candidates {reference index, motionvalues} is built and a merge index identifying one candidate is signaledto acquire motion information for the motion compensated interprediction) with another prediction P1 that is one of an intraprediction (MH-inter-intra) or another inter prediction (MH-inter-intere.g. uni-prediction AMVP, skip and merge). The final prediction is theweighted average of the merge indexed prediction and the predictiongenerated by the other prediction mode (intra or inter), where differentweights are applied depending on the combinations.

FIG. 5 illustrates of an example of a multi-hypothesis prediction incase of inter and intra modes combination MH-inter-intra. The intraprediction mode is signaled (it can be a subset (e.g. 4) of classicalprediction modes), The weights w_intra(y) gradually decrease as theregion is far from the intra reference samples. According to anon-limiting example, the current block is split into 4 equal-arearegions sharing same weighting. Each weight set, denoted as(w0=w_intra_(i), w1=w_inter_(i)), where i is from 1 to 4 and (w_intra₁,w_inter₁)=(6, 2), (w_intra₂, w_inter₂)=(5, 3), (w_intra₃, w_inter₃)=(3,5), and (w_intra₄, w_inter₄)=(2, 6), are applied to a correspondingregion, as depicted in example of FIG. 5 for intra vertical directionprediction. When DC or planar mode is selected, or the CU width orheight is smaller than 4, equal weights are applied. In other words,when the intra prediction mode of the prediction P1 is DC or planarmode, the relative weight used in the prediction of any sample of thecurrent block is w0=w_intra=½ and w1=w_inter=½. Accordingly, there isonly one region of equal weight (i=1). The coding mode Combined Intermerge Intra Prediction CIIP defined in WC is a particular example ofMH-Inter-Intra that combines an inter prediction P0 (which can beuni-directional or bi-predicted) performed in merge mode with anotherprediction P1 that is a planar intra prediction with equal weight ½.

According to another example of a multi-hypothesis prediction in case ofinter and inter modes combination MH-inter-inter, the weights aredefault ones (½; ½). According to other variant examples ofMH-inter-inter mode, one or two of the inter modes is bi-prediction {2MVs, 2 references}, so that the building of the sample predictionsrequires the computation of up to 4 motion compensations.

A Third Prediction Mode for which Deblocking Filter is Adapted:Geometric Partitioning

The geometric (e.g. triangular) modes allows more flexibility forpartitioning the picture into blocks before coding. FIG. 6 illustratesexamples of a non-rectangular partitioning (top) and an example ofoverlap block motion compensation diagonal weighting associated to atriangle partitioning (bottom). The 2 left examples on the top of FIG. 6represents triangle partitions while the 4 right examples on the top ofFIG. 6 represents more generic schemes of geometric partitioning.Additional coding performance is obtained when blending overlappedboundaries for instance along the diagonal edge as shown on the bottomof FIG. 6 . Accordingly, a luma sample with a weighting factor of 4located on the diagonal of the block uses equal weights of ½ (W₁=W₂=4/8=½) while a luma sample neighboring the diagonal of the block with aweighting factor of 2 uses weights of (W₁= 2/8=¼ and W₂= 6/8=¾). In somevariant examples, this weighting process cascades with other weightingssuch as GBI or Local Illumination Compensation LIC and increases theimplementation complexity.

In case of Triangle partitioning, the samples can be split in 2 groups:

-   -   Samples predicted with uni-directional motion-compensation (P0        or P1)    -   Samples predicted with bi-prediction motion-compensation,        blending of uni-directional prediction P0 and uni-directional        prediction P1.

As previously explained at least theses 3 coding modes with weightedprediction raises issue while assessing the boundary strength or filterstrength in a deblocking filter.

Several Embodiments of a Modified Deblocking Filter Adapted to NewPrediction Modes

At least one embodiment of the present principles relates to modifyingthe deblocking filter DBF in the case the blocks are encoded usingcombination of non-square or non-rectangular blocks (e.g. Triangle)and/or the combination of unequal (e.g. GBi) and/or spatially variableweighting (e.g. MH). Advantageously, the non-square or non-rectangularblocks, as illustrated for the triangle partition or more generally forgeometric partition, are considered as a combination of 2 predictionswith spatially variable weighting as illustrated on FIG. 7 .

Advantageously, in at least one embodiment, the DBF process (filterstrength derivation and filtering) is modified to keep the original DBFintent and efficiency and thus increases its efficiency compared toprior art methods.

FIG. 8 illustrates an example of a method for deblocking a part of animage according to a general aspect of at least one embodiment.According to a preliminary step S110, information relative to 2neighboring blocks is accessed. The 2 neighboring blocks are tatter oncalled a first block P and a second block Q and they are interchangeablewithout restriction. The terms first and second may be used herein todescribe 2 blocks, these 2 blocks should not be limited by these terms.These terms are only used to distinguish one element from another. Thefirst block P and second block Q belongs to the part of the image tofilter. A block of samples is, according to non-limiting examples, oneof Coding Unit or a Transform Unit. In a first step S120, at least oneboundary between the first block P of samples and the second block Q ofsamples is determined. In a particular embodiment, a flag EdgeFlag isset to one for a sample at a boundary to filter with DBF and the flagEdgeFlag is set to zero for a sample that is not to be filtered withDBF. A sample that is not to be filtered with DBF comprises a sample atthe boundary of the image or at the boundary of a slice or a sampleinside (not a boundary sample) a block, e.g. a coding unit or atransform unit. A boundary is either a horizontal boundary (horizontaledge) or a vertical boundary (vertical edge). In a step S130, at leastone parameter of the DBF is determined. As previously exposed, the atleast one parameter of the DBF comprises the boundary strength BS of thefilter, and the filter strength FS. The boundary strength BS is selectedamong weak (BS=0), normal (BS=1), or strong (BS=2) values. The filterstrength FS refers to the result of a decision process regardingapplying the filter or not and affecting more or less pixels on eachside of the block boundary. The decision process comprises at least onecondition on the value of samples of the first block P and the secondblock Q. In a step S140, the boundary strength BS is determinedaccording to at least one of a prediction mode of the first block and aprediction mode of the second block.

Advantageously, the boundary strength BS is adapted for prediction modebeing a weighted prediction mode combining a first prediction with asecond prediction. According to a particular characteristic, in case theprediction mode of the first block is a weighted prediction mode, theboundary strength BS further depends on the relative weight of samplesused in predicting the first block of samples according to the weightedprediction mode of the first block. According to a particularcharacteristic, a weighted prediction mode is one of the previouslydescribed coding mode comprising a Generalized Bi-prediction GBi alsoreferred to as Bi-prediction with Coding Units level Weights BCW, aMulti-Hypothesis prediction combining intra and inter predicted samplesMH-inter-intra or combining inter and inter predicted samplesMH-inter-inter, a Combined Inter merge intra Prediction combining intermerge and intra predicted samples, a Geometric prediction combininginter predicted samples according to a geometric partition of a block, aTriangle prediction combining inter predicted samples along a diagonaledge of a block. Various embodiments for determining the BS areexplained here after.

According to a particular embodiment wherein predicting the first blockof samples according to a weighted prediction mode of the first blockcomprises predicting a sample of the first block as weighted combination(w0, w1=1−w0) of a first predictor P0 determined using a firstprediction mode and of a second predictor P1 determined using a secondprediction mode, and wherein the sample of the first block is consideredas using the first prediction mode for determining the boundary strengthin case the weight w0 of a first predictor is above a level.

According to other particular embodiment, the number of samples in theblock with the weight w0 of a first predictor is above a leveldetermines the mode to use for the first black in BS.

According to a particular, variant the level is set to zero. Accordingto another particular variant, the boundary strength is determined for agroup of samples of the block sharing a same relative weight. Accordingto non-limiting examples, a group of samples comprises one sample, or4×4 samples and up to all samples of the block. Then in a step S160, theDBF filtering process is applied to the first and second block along theboundary according to the determined boundary strength BS.

In previous approach, the choice of DBF parameters for one rectangularor square block is carried-out for each set of line (or column) sampleson each side of a vertical (resp. horizontal) boundary {p_(3i), p_(2i),p_(1i), p_(0i), q_(0i), q_(1i), q_(2i), q_(3i)} as illustrated on FIG. 2. However, to facilitate implementation it is generally preferred tomanage/set the DBF parameters per group of samples such as 4×4sub-blocks for example.

Accordingly, in the following, the embodiments are described in the casewhere DBF parameters for the current block are set per group of samplesof size 4×4 sub-blocks. However, the present principles are not limitedto determining DBF parameters for 4×4 sub-blocks. The skilled in the artwill straightforwardly deduce parameter from the below examples forother size or even per single line (or single column). Then, the blockis partitioned into a set of sub-blocks and the same DBF parameters(e.g. BS) are derived for all the samples of the sub-blocks, except theDBF parameters (e.g. filtering strength) related to the sample values inone line (resp. column).

FIG. 7 illustrates of an example of a triangle logical partitioning(left) and a blending map (right) according to a particular embodiment.In case of non-rectangular partitioning such as Triangles for example,it may happen some samples of one sub-block are predicted withuni-directional prediction and others are predicted with bi-prediction(blending of two uni-directional predictions). On the left of FIG. 7 ,the subblock sb2 illustrates a sub-block predicted with uni-directionalprediction while subblock sb3 illustrates a sub-block predicted withbi-prediction. In this case, if the choice of BS is made individuallyfor each sample, the BS may be different per sample because the steps320,330,340 may give different results.

In the following, we will associate to each sub-block two blending mapswhich contains for each sample (x) the blending weights w0(x) and w1(x)associated to the first predictor block P0 and the second predictorblock P1 respectively. The purpose of this map is to facilitate thedescription of the embodiments and then it may be virtual, meaning itmay be not computed or stored in memory system. In case of traditionalbi-prediction, the 2 maps are uniform equal to ½. In case of GBi, the 2maps are uniform equal to ⅜ and ⅝ respectively for example. In case ofMH, w0(x)=w_intra(x) and w1(x)=w_inter(x) for example.

Several embodiments are described for determining the boundary strengthBS used in the generic method for deblocking a part of an image, theembodiments may be arranged together according to any combination of theseveral embodiments.

A First Embodiment of Deblocking Filter

The first embodiment comprises a deblocking filter wherein the boundarystrength is adapted to the number of samples and the relative weight ofsamples used in bi-prediction or weighed bi-prediction. This embodimentis advantageously well adapted in case one sub-block on one side of theboundary uses geometric partition or GBi.

For a given sub-block, the process 320 of FIG. 3 is modified as follows:

-   -   a) if at least one sample in the sub-block is bi-predicted, then        the sub-block is considered as bi-predicted for the        determination of BS (as for instance sb2 and sb3 according to        the blending map of the right of FIG. 7 ).    -   b) In a variant, if the relative number of samples using        bi-prediction in the sub-block is superior to a threshold, then        the sub-block is considered as bi-predicted for the        determination of BS (for instance sb3, having 14 bi-predicted        samples according to the blending map of the right of FIG. 7 ,        is considered as bi-predicted while sb2, having 3 bi-predicted        samples according to the blending map of the right of FIG. 7 ,        is considered as unidirectional predicted).    -   c) In a variant, the computation of the number of bi-predicted        samples in the sub-block excludes the samples for which one        blending weight (w0(x) or w1(x)) is below a threshold or level        (e.g. th=¼). These samples are considered as unidirectional        predicted.    -   d) In a variant, let denote n0 the relative number of samples        using reference 0 for the prediction and let denote n1 the        relative number of samples using the reference 1 for the        prediction, if n0/(n0+n1) and n1/(n0+n1) are superior to a        threshold, then the sub-block is considered as bi predicted for        the determination of BS.

According to a non-limiting value, in b), c) and d), threshold or levelis zero.

Advantageously, the threshold is, for instance, hard coded inside a LookUp Table indexed by the size of the block and the partition type.

A Second Embodiment of Deblocking Filter

The second embodiment comprises a deblocking filter wherein the boundarystrength is locally adapted to the relative weight of samples used incombining inter and intra predicted samples or in combining inter andinter predicted samples. This embodiment is advantageously well adaptedin case one sub-block on one side of the boundary uses MH.

Considering a sub-block using MH-inter-intra:

-   -   a) the areas of the block where w_intra(x) is superior to a        threshold/level are considered as intra. For example, in case of        the MH-inter-intra example of FIG. 5 , the first 3 top areas are        considered as intra.    -   b) the areas of the block where w_inter(x) is superior to a        threshold/level are considered as inter. If the inter-prediction        is bi-prediction (or uni-directional), the area is considered        bi-prediction (resp. uni-directional). For example, in case of        the MH-inter-intra example of FIG. 5 , the last bottom area        (w_inter(x)= 6/8) is considered as inter.

Note that as previously, in a variant, the threshold or level is zero.

Besides, in a variant, the threshold is hard coded inside a Look UpTable indexed by the size of the block and the intra direction used.

Thus, according to a), in case the first prediction mode is one intraprediction mode and in case the weight of the first predictor(w_intra(x)) is above a level, the sample of the first block isconsidered as using intra prediction mode for determining the boundarystrength. In particular, this applies to any of the intra predictionmodes including directional intra prediction (for instance verticalintra prediction as illustrated on FIG. 5 ) and non-directional modesuch as DC or planar. Besides, in case of planar or DC mode, equalweights are applied for the whole area of the block resulting in a sameintra prediction mode for the whole area of the block. According to theoriginal DBF intent, BS is set to strong (BS=2) in case the first blockP or second block Q is Intra, thus in case the first prediction mode isone intra prediction mode and in case the weight of the first predictor(w_intra(x)) is above a level, the boundary strength is set to strong.In a particular variant corresponding to CIIP (MH-Inter-Intra whereinintra is planar), BS is set to strong (BS=2) for the block.

Besides, according to b), in case the first prediction mode is one interprediction mode and in case the weight of the first predictor(w_inter(x)) is above a level, the sample of the first block isconsidered as using inter prediction mode for determining the boundarystrength. In particular, this applies to any of the inter predictionmodes including uni-directional and bi-directional inter prediction.Accordingly, in case the first prediction mode is an interbi-directional prediction mode then the sample of the first block isconsidered as using inter bi-directional prediction mode for determiningthe boundary strength, and respectively in case the first predictionmode is an inter uni-directional prediction mode, the sample of thefirst block is considered as using inter uni-directional prediction modefor determining the boundary strength. Then, different variant checks,regarding the reference index and motion vector differences areprocessed according to the bidirectional or unidirectional interprediction mode.

Considering a sub-block using MH-inter-inter, with P0 bi-predicted andP1 uni-directional predicted:

-   -   c) the areas of the block where w0(x) is superior to a        threshold/level are considered as bi-predicted, while the areas        of the block where w1(x) is superior to a threshold are        considered as uni-predicted.    -   d) In a variant, if at least P0 or P1 is bi-predicted and        {w0(x);w1(x)} are both superior to a threshold, then check.1 and        check.2 are changed as:

if for all pair values of (i;j):ref-i _(P)≠ref-j ₀  (check.1)

if for one pair value (i;j) with ref-i _(P)=ref-j _(Q):|MVi _(P)−MVj_(Q)|>threshold  (check.2)

-   -   with (i;j) such as ref-i_(P)>=0 and ref-j_(Q)>=0

Note that as previously, in a variant, the threshold or level is zero.

Advantageously, the threshold can be hard coded inside a Look Up Tableindexed by the size of the block and the partition type.

A Third Embodiment of Deblocking Filter

The third embodiment comprises a deblocking filter wherein the boundarystrength is adapted to the weight of samples used in the prediction.This embodiment is advantageously well adapted in case one sub-block onone side of the boundary uses Generalized Bi-prediction GBi or BCW.

Considering a sub-block where the GBi weights (w0(x);w1(w)) associatedto reference-0 and reference-1 are not defaults:

-   -   a) If w0(x) or w1(x) is inferior to a threshold, then the block        is considered as uni-directional prediction {MV1,ref-1} (or        MV0,ref-0 resp.) in steps (320,330), and only {MV1,ref-1} (or        MV0,ref-0 resp.) is used in (340).

A Fourth Embodiment of Deblocking Filter

The fourth embodiment comprises a deblocking filter wherein the motionvectors are normalized with POC difference for determining boundarystrength. In case the first block P and the second block Q havedifferent reference indexes, test (320) is inferred to “false” and for(340) the MV value of Q (or P) is re-scaled to same POC as P (or Qrespectively).

A Fifth Embodiment of Deblocking Filter

The fifth embodiment comprises a deblocking filter wherein determiningboundary strength comprises a test (additional condition) on whether thecoding mode of one of the blocks at boundary is at least one of MH, GBi,bi-prediction.

FIG. 9 illustrates a flowchart of a determination of the BoundaryStrength in a deblocking filter method according to the fifthembodiment. The determination of BS (300) is modified to include anadditional condition (315) on the coding mode (XX) of the first block Por the second block Q. If the determination of BS follows the schemedescribed in FIG. 3 , this additional condition may be placedbefore/after/in-between one of the conditions (310,320,330,340) asdepicted in one non-limiting example in FIG. 9 . According tonon-limiting examples, XX is MH and/or GBi and/or bi-prediction.According to others non-limiting examples, determining the coding mode(XX) of the first block P or the second block Q is compatible with anyof the variants described for the first, the second or third embodiment.For instance, the coding mode of a block is determined based on thenumber of samples and relative weight of samples used in bi-prediction,the coding mode of a block is determined based on the relative weight ofsamples used in MH. In case a coding mode Is determined as Intra, the BSis set to 2.

A Sixth Embodiment of Deblocking Filter

The sixth embodiment comprises encoder/decoder wherein coding parametersare modified and stored at the decoding/reconstructing for subsequentuse in the deblocking filter (in determining of boundary strengthparameter). FIG. 10 illustrates 2 flowcharts of the storing of CUparameters used in the determination of the Boundary Strength (BS)parameter in a deblocking filter method according to particularembodiments. The method for deblocking 500 a part of an image of theleft and right of FIG. 10 is implemented in the in-loop filtering of anencoder or decoder. The method comprises a step 330 of determination ofBS and a step 400 of application of the filter DBF.

In an embodiment represented on the left of FIG. 10 , the determinationof the BS parameters depends on a subset of CU (or sub-CU) parameters(e.g. P,Q modes, reference indexes, MV values) and is modified accordingto the previously exposed embodiments. In another embodiment representedon the right of FIG. 10 , the determination of the BS parameters 300 isunchanged but some of this subset of CU (or sub-CU) parameters aremodified 530 after their use for decoding 510 and reconstructing 520 thecurrent CU (resp. sub-CU) and stored to be available by other process(e.g. DBF process). The modification of this subset of CU parameters isfunction of other decoded CU parameters 515. Therefore, this functionallows making the value of BS (output of 300) depending on otherparameters than the decoded subset of CU (or sub-CU) parameters.

For example, if coding mode is MH-inter-intra, and if w_intra(x) issuperior to a threshold, then the coding mode is modified as intrabefore storage, so that in 300 the BS is set to strong (BS=2)corresponding to intra prediction mode. In this way, one obtains samebehavior as described the variant a) of the second embodiment relativeto MH-inter-intra or CIIP.

In another example, if the relative number of samples usingbi-prediction in the sub-block is superior to a threshold, then thesub-block the coding mode is modified as bi-predicted before storage, sothat in step 300, the current CU is set as bi-predicted, one obtainssame behavior as described in the variant b) of the first embodiment.

In a variant, these modified CU (or sub-CU) parameters stored for lateruse, are used by other CU (or sub-CUs) for another process than DBF. Forexample, the modified MV values can be later used for temporal motionprediction (e.g. ATMVP).

Additional Embodiments and Information

This application describes a variety of aspects, including tools,features, embodiments, models, approaches, etc. Many of these aspectsare described with specificity and, at least to show the individualcharacteristics, are often described in a manner that may soundlimiting. However, this is for purposes of clarity in description, anddoes not limit the application or scope of those aspects. Indeed, all ofthe different aspects can be combined and interchanged to providefurther aspects. Moreover, the aspects can be combined and interchangedwith aspects described in earlier filings as well.

The aspects described and contemplated in this application can beimplemented in many different forms. FIGS. 11, 12 and 13 below providesome embodiments, but other embodiments are contemplated and thediscussion of FIGS. 11, 12 and 13 does not limit the breadth of theimplementations. At least one of the aspects generally relates to videoencoding and decoding, and at least one other aspect generally relatesto transmitting a bitstream generated or encoded. These and otheraspects can be implemented as a method, an apparatus, a computerreadable storage medium having stored thereon instructions for encodingor decoding video data according to any of the methods described, and/ora computer readable storage medium having stored thereon a bitstreamgenerated according to any of the methods described.

In the present application, the terms “reconstructed” and “decoded” maybe used interchangeably, the terms “pixel” and “sample” may be usedinterchangeably, the terms “image,” “picture” and “frame” may be usedinterchangeably. Usually, but not necessarily, the term “reconstructed”is used at the encoder side while “decoded” is used at the decoder side.

Various methods are described herein, and each of the methods comprisesone or more steps or actions for achieving the described method. Unlessa specific order of steps or actions is required for proper operation ofthe method, the order and/or use of specific steps and/or actions may bemodified or combined.

Various methods and other aspects described in this application can beused to modify modules, for example, the in-loop filters (165, 265) of avideo encoder 100 and decoder 200 as shown in FIG. 11 and FIG. 12 .Moreover, the present aspects are not limited to WC or HEVC, and can beapplied, for example, to other standards and recommendations, whetherpre-existing or future-developed, and extensions of any such standardsand recommendations (including WC and HEVC). Unless indicated otherwise,or technically precluded, the aspects described in this application canbe used individually or in combination.

Various numeric values are used in the present application, for example,the size of the sub-block 4×4 on which the DBF parameters are estimated.The specific values are for example purposes and the aspects describedare not limited to these specific values.

FIG. 11 illustrates an encoder 100. Variations of this encoder 100 arecontemplated, but the encoder 100 is described below for purposes ofclarity without describing all expected variations.

Before being encoded, the video sequence may go through pre-encodingprocessing (101), for example, applying a color transform to the inputcolor picture (e.g., conversion from RGB 4:4:4 to YCbCr 4:2:0), orperforming a remapping of the input picture components in order to get asignal distribution more resilient to compression (for instance using ahistogram equalization of one of the color components). Metadata can beassociated with the pre-processing, and attached to the bitstream.

In the encoder 100, a picture is encoded by the encoder elements asdescribed below. The picture to be encoded is partitioned (102) andprocessed in units of, for example, CUs. Each unit is encoded using, forexample, either an intra or inter mode. When a unit is encoded in anintra mode, it performs intra prediction (160). In an inter mode, motionestimation (175) and compensation (170) are performed. The encoderdecides (105) which one of the intra mode or inter mode to use forencoding the unit, and indicates the intra/inter decision by, forexample, a prediction mode flag. Prediction residuals are calculated,for example, by subtracting (110) the predicted block from the originalimage block.

The prediction residuals are then transformed (125) and quantized (130).The quantized transform coefficients, as well as motion vectors andother syntax elements, are entropy coded (145) to output a bitstream.The encoder can skip the transform and apply quantization directly tothe non-transformed residual signal. The encoder can bypass bothtransform and quantization, i.e., the residual is coded directly withoutthe application of the transform or quantization processes.

The encoder decodes an encoded block to provide a reference for furtherpredictions. The quantized transform coefficients are de-quantized (140)and inverse transformed (150) to decode prediction residuals. Combining(155) the decoded prediction residuals and the predicted block, an imageblock is reconstructed. In-loop filters (165) are applied to thereconstructed picture to perform, for example, deblocking/SAO (SampleAdaptive Offset) filtering to reduce encoding artifacts. The filteredimage is stored at a reference picture buffer (180).

FIG. 12 illustrates a block diagram of a video decoder 200. In thedecoder 200, a bitstream is decoded by the decoder elements as describedbelow. Video decoder 200 generally performs a decoding pass reciprocalto the encoding pass as described in FIG. 11 . The encoder 100 alsogenerally performs video decoding as part of encoding video data.

In particular, the input of the decoder includes a video bitstream,which can be generated by video encoder 100, The bitstream is firstentropy decoded (230) to obtain transform coefficients, motion vectors,and other coded information. The picture partition information indicateshow the picture is partitioned. The decoder may therefore divide (235)the picture according to the decoded picture partitioning information.The transform coefficients are de-quantized (240) and inversetransformed (250) to decode the prediction residuals. Combining (255)the decoded prediction residuals and the predicted block, an image blockis reconstructed. The predicted block can be obtained (270) from intraprediction (260) or motion-compensated prediction (i.e., interprediction) (275). In-loop filters (265) are applied to thereconstructed image. The filtered image is stored at a reference picturebuffer (280).

The decoded picture can further go through post-decoding processing(285), for example, an inverse color transform (e.g. conversion fromYCbCr 4:2:0 to RGB 4:4:4) or an inverse remapping performing the inverseof the remapping process performed in the pre-encoding processing (101).The post-decoding processing can use metadata derived in thepre-encoding processing and signaled in the bitstream.

FIG. 13 illustrates a block diagram of an example of a system in whichvarious aspects and embodiments are implemented. System 1000 can beembodied as a device including the various components described belowand is configured to perform one or more of the aspects described inthis document. Examples of such devices, include, but are not limitedto, various electronic devices such as personal computers, laptopcomputers, smartphones, tablet computers, digital multimedia set topboxes, digital television receivers, personal video recording systems,connected home appliances, and servers. Elements of system 1000, singlyor in combination, can be embodied in a single integrated circuit (IC),multiple ICs, and/or discrete components. For example, in at least oneembodiment, the processing and encoder/decoder elements of system 1000are distributed across multiple ICs and/or discrete components. Invarious embodiments, the system 1000 is communicatively coupled to oneor more other systems, or other electronic devices, via, for example, acommunications bus or through dedicated input and/or output ports. Invarious embodiments, the system 1000 is configured to implement one ormore of the aspects described in this document.

The system 1000 includes at least one processor 1010 configured toexecute instructions loaded therein for implementing, for example, thevarious aspects described in this document. Processor 1010 can includeembedded memory, input output interface, and various other circuitriesas known in the art. The system 1000 includes at least one memory 1020(e.g., a volatile memory device, and/or a non-volatile memory device).System 1000 includes a storage device 1040, which can includenon-volatile memory and/or volatile memory, including, but not limitedto, Electrically Erasable Programmable Read-Only Memory (EEPROM),Read-Only Memory (ROM), Programmable Read-Only Memory (PROM), RandomAccess Memory (RAM), Dynamic Random Access Memory (DRAM), Static RandomAccess Memory (SRAM), flash, magnetic disk drive, and/or optical diskdrive. The storage device 1040 can include an internal storage device,an attached storage device (including detachable and non-detachablestorage devices), and/or a network accessible storage device, asnon-limiting examples.

System 1000 includes an encoder/decoder module 1030 configured, forexample, to process data to provide an encoded video or decoded video,and the encoder/decoder module 1030 can include its own processor andmemory. The encoder/decoder module 1030 represents module(s) that can beincluded in a device to perform the encoding and/or decoding functions.As is known, a device can include one or both of the encoding anddecoding modules. Additionally, encoder/decoder module 1030 can beimplemented as a separate element of system 1000 or can be incorporatedwithin processor 1010 as a combination of hardware and software as knownto those skilled in the art.

Program code to be loaded onto processor 1010 or encoder/decoder 1030 toperform the various aspects described in this document can be stored instorage device 1040 and subsequently loaded onto memory 1020 forexecution by processor 1010. In accordance with various embodiments, oneor more of processor 1010, memory 1020, storage device 1040, andencoder/decoder module 1030 can store one or more of various itemsduring the performance of the processes described in this document. Suchstored items can include, but are not limited to, the input video, thedecoded video or portions of the decoded video, the bitstream, matrices,variables, and intermediate or final results from the processing ofequations, formulas, operations, and operational logic.

In some embodiments, memory inside of the processor 1010 and/or theencoder/decoder module 1030 is used to store instructions and to provideworking memory for processing that is needed during encoding ordecoding. In other embodiments, however, a memory external to theprocessing device (for example, the processing device can be either theprocessor 1010 or the encoder/decoder module 1030) is used for one ormore of these functions. The external memory can be the memory 1020and/or the storage device 1040, for example, a dynamic volatile memoryand/or a non-volatile flash memory. In several embodiments, an externalnon-volatile flash memory is used to store the operating system of, forexample, a television.

In at least one embodiment, a fast external dynamic volatile memory suchas a RAM is used as working memory for video coding and decodingoperations, such as for MPEG-2 (MPEG refers to the Moving PictureExperts Group, MPEG-2 is also referred to as ISO/IEC 13818, and 13818-1is also known as H.222, and 13818-2 is also known as H.262). HEVC (HEVCrefers to High Efficiency Video Coding, also known as H.265 and MPEG-HPart 2), or VVC (Versatile Video Coding, a new standard being developedby JVET, the Joint Video Experts Team).

The input to the elements of system 1000 can be provided through variousinput devices as indicated in block 1130. Such input devices include,but are not limited to, (i) a radio frequency (RF) portion that receivesan RF signal transmitted, for example, over the air by a broadcaster,(ii) a Component (COMP) input terminal (or a set of COMP inputterminals), (iii) a Universal Serial Bus (USB) input terminal, and/or(iv) a High Definition Multimedia Interface (NOMI) input terminal. Otherexamples, not shown in FIG. 13 , include composite video.

In various embodiments, the input devices of block 1130 have associatedrespective input processing elements as known in the art. For example,the RF portion can be associated with elements suitable for (i)selecting a desired frequency (also referred to as selecting a signal,or band-limiting a signal to a band of frequencies). (ii) downconvertingthe selected signal, (iii) band-limiting again to a narrower band offrequencies to select (for example) a signal frequency band which can bereferred to as a channel in certain embodiments, (iv) demodulating thedownconverted and band-limited signal. (v) performing error correction,and (vi) demultiplexing to select the desired stream of data packets.The RF portion of various embodiments includes one or more elements toperform these functions, for example, frequency selectors, signalselectors, band-limiters, channel selectors, filters, downconverters,demodulators, error correctors, and demultiplexers. The RF portion caninclude a tuner that performs various of these functions, including, forexample, downconverting the received signal to a lower frequency (forexample, an intermediate frequency or a near-baseband frequency) or tobaseband. In one set-top box embodiment, the RF portion and itsassociated input processing element receives an RF signal transmittedover a wired (for example, cable) medium, and performs frequencyselection by filtering, downconverting, and filtering again to a desiredfrequency band. Various embodiments rearrange the order of theabove-described (and other) elements, remove some of these elements,and/or add other elements performing similar or different functions.Adding elements can include inserting elements in between existingelements, such as, for example, inserting amplifiers and ananalog-to-digital converter. In various embodiments, the RF portionincludes an antenna.

Additionally, the USB and/or HDMI terminals can include respectiveinterface processors for connecting system 1000 to other electronicdevices across USB and/or HOW connections. It is to be understood thatvarious aspects of input processing, for example, Reed-Solomon errorcorrection, can be implemented, for example, within a separate inputprocessing IC or within processor 1010 as necessary. Similarly, aspectsof USB or HDMI interface processing can be implemented within separateinterface ICs or within processor 1010 as necessary. The demodulated,error corrected, and demultiplexed stream is provided to variousprocessing elements, including, for example, processor 1010, andencoder/decoder 1030 operating in combination with the memory andstorage elements to process the datastream as necessary for presentationon an output device.

Various elements of system 1000 can be provided within an integratedhousing. Within the integrated housing, the various elements can beinterconnected and transmit data therebetween using suitable connectionarrangement, for example, an internal bus as known in the art, includingthe Inter-IC (I2C) bus, wiring, and printed circuit boards.

The system 1000 includes communication interface 1050 that enablescommunication with other devices via communication channel 1060. Thecommunication interface 1050 can include, but is not limited to, atransceiver configured to transmit and to receive data overcommunication channel 1060. The communication interface 1050 caninclude, but is not limited to, a modem or network card and thecommunication channel 1060 can be implemented, for example, within awired and/or a wireless medium.

Data is streamed, or otherwise provided, to the system 1000, in variousembodiments, using a wireless network such as a Wi-Fi network, forexample IEEE 802.11 (IEEE refers to the Institute of Electrical andElectronics Engineers). The Wi-Fi signal of these embodiments isreceived over the communications channel 1060 and the communicationsinterface 1050 which are adapted for Wi-Fi communications. Thecommunications channel 1060 of these embodiments is typically connectedto an access point or router that provides access to external networksincluding the Internet for allowing streaming applications and otherover-the-top communications. Other embodiments provide streamed data tothe system 1000 using a set-top box that delivers the data over the HDMIconnection of the input block 1130. Still other embodiments providestreamed data to the system 1000 using the RF connection of the inputblock 1130. As indicated above, various embodiments provide data in anon-streaming manner, Additionally, various embodiments use wirelessnetworks other than for example a cellular network or a Bluetoothnetwork.

The system 1000 can provide an output signal to various output devices,including a display 1100, speakers 1110, and other peripheral devices1120. The display 1100 of various embodiments includes one or more of,for example, a touchscreen display, an organic light-emitting diode(OLED) display, a curved display, and/or a foldable display. The display1100 can be for a television, a tablet, a laptop, a cell phone (mobilephone), or other device. The display 1100 can also be integrated withother components (for example, as in a smart phone), or separate (forexample, an external monitor for a laptop). The other peripheral devices1120 include, in various examples of embodiments, one or more of astand-alone digital video disc (or digital versatile disc) (DVR, forboth terms), a disk player, a stereo system, and/or a lighting system.Various embodiments use one or more peripheral devices 1120 that providea function based on the output of the system 1000. For example, a diskplayer performs the function of playing the output of the system 1000.

In various embodiments, control signals are communicated between thesystem 1000 and the display 1100, speakers 1110, or other peripheraldevices 1120 using signaling such as AV.Link, Consumer ElectronicsControl (CEC), or other communications protocols that enabledevice-to-device control with or without user intervention. The outputdevices can be communicatively coupled to system 1000 via dedicatedconnections through respective interfaces 1070, 1080, and 1090.Alternatively, the output devices can be connected to system 1000 usingthe communications channel 1060 via the communications interface 1050.The display 1100 and speakers 1110 can be integrated in a single unitwith the other components of system 1000 in an electronic device suchas, for example, a television. In various embodiments, the displayinterface 1070 includes a display driver, such as, for example, a timingcontroller (T Con) chip.

The display 1100 and speaker 1110 can alternatively be separate from oneor more of the other components, for example, if the RF portion of input1130 is part of a separate set-top box. In various embodiments in whichthe display 1100 and speakers 1110 are external components, the outputsignal can be provided via dedicated output connections, including, forexample, HDMI ports, USB ports, or COMP outputs.

The embodiments can be carried out by computer software implemented bythe processor 1010 or by hardware, or by a combination of hardware andsoftware. As a non-limiting example, the embodiments can be implementedby one or more integrated circuits. The memory 1020 can be of any typeappropriate to the technical environment and can be implemented usingany appropriate data storage technology, such as optical memory devices,magnetic memory devices, semiconductor-based memory devices, fixedmemory, and removable memory, as non-limiting examples. The processor1010 can be of any type appropriate to the technical environment, andcan encompass one or more of microprocessors, general purpose computers,special purpose computers, and processors based on a multi-corearchitecture, as non-limiting examples.

Various implementations involve decoding. “Decoding”, as used in thisapplication, can encompass all or part of the processes performed, forexample, on a received encoded sequence in order to produce a finaloutput suitable for display. In various embodiments, such processesinclude one or more of the processes typically performed by a decoder,for example, entropy decoding, inverse quantization, inversetransformation, and differential decoding. In various embodiments, suchprocesses also, or alternatively, include processes performed by adecoder of various implementations described in this application, forexample, reconstructing a picture, determining parameters of adeblocking filter and then filtering the reconstructed picture withdetermined deblocking filter parameters.

As further examples, in one embodiment “decoding” refers only to entropydecoding, in another embodiment “decoding” refers only to differentialdecoding, and in another embodiment “decoding” refers to a combinationof entropy decoding and differential decoding. Whether the phrase“decoding process” is intended to refer specifically to a subset ofoperations or generally to the broader decoding process will be clearbased on the context of the specific descriptions and is believed to bewell understood by those skilled in the art.

Various implementations involve encoding. In an analogous way to theabove discussion about “decoding”, “encoding” as used in thisapplication can encompass all or part of the processes performed, forexample, on an input video sequence in order to produce an encodedbitstream. In various embodiments, such processes include one or more ofthe processes typically performed by an encoder, for example,partitioning, differential encoding, transformation, quantization, andentropy encoding. In various embodiments, such processes also, oralternatively, include processes performed by an encoder of variousimplementations described in this application, for example,reconstructing an encoded picture, determining parameters of adeblocking filter and then filtering the reconstructed picture withdetermined deblocking filter parameters.

As further examples, in one embodiment “encoding” refers only to entropyencoding, in another embodiment “encoding” refers only to differentialencoding, and in another embodiment “encoding” refers to a combinationof differential encoding and entropy encoding. Whether the phrase“encoding process” is intended to refer specifically to a subset ofoperations or generally to the broader encoding process will be clearbased on the context of the specific descriptions and is believed to bewell understood by those skilled in the art.

Note that the syntax elements as used herein, for example, aredescriptive terms. As such, they do not preclude the use of other syntaxelement names.

When a figure is presented as a flow diagram, it should be understoodthat it also provides a block diagram of a corresponding apparatus.Similarly, when a figure is presented as a block diagram, it should beunderstood that it also provides a flow diagram of a correspondingmethod/process.

The implementations and aspects described herein can be implemented in,for example, a method or a process, an apparatus, a software program, adata stream, or a signal. Even if only discussed in the context of asingle form of implementation (for example, discussed only as a method),the implementation of features discussed can also be implemented inother forms (for example, an apparatus or program). An apparatus can beimplemented in, for example, appropriate hardware, software, andfirmware. The methods can be implemented in, for example, a processor,which refers to processing devices in general, including, for example, acomputer, a microprocessor, an integrated circuit, or a programmablelogic device. Processors also include communication devices, such as,for example, computers, cell phones, portable/personal digitalassistants (“PDAs”), and other devices that facilitate communication ofinformation between end-users.

Reference to “one embodiment” or “an embodiment” or “one implementation”or “an implementation”, as well as other variations thereof, means thata particular feature, structure, characteristic, and so forth describedin connection with the embodiment is included in at least oneembodiment. Thus, the appearances of the phrase “in one embodiment” or“in an embodiment” or “in one implementation” or “in an implementation”,as well any other variations, appearing in various places throughoutthis application are not necessarily all referring to the sameembodiment.

Additionally, this application may refer to “determining” various piecesof information. Determining the information can include one or more of,for example, estimating the information, calculating the information,predicting the information, or retrieving the information from memory.

Further, this application may refer to “accessing” various pieces ofinformation. Accessing the information can include one or more of, forexample, receiving the information, retrieving the information (forexample, from memory), storing the information, moving the information,copying the information, calculating the information, determining theinformation, predicting the information, or estimating the information.

Additionally, this application may refer to “receiving” various piecesof information. Receiving is, as with “accessing”, intended to be abroad term. Receiving the information can include one or more of, forexample, accessing the information, or retrieving the information (forexample, from memory). Further, “receiving” is typically involved, inone way or another, during operations such as, for example, storing theinformation, processing the information, transmitting the information,moving the information, copying the information, erasing theinformation, calculating the information, determining the information,predicting the information, or estimating the information.

It is to be appreciated that the use of any of the following “/”,“and/or”, and “at least one of”, for example, in the cases of “A/B”. “Aand/or B” and “at least one of A and B”, is intended to encompass theselection of the first listed option (A) only, or the selection of thesecond listed option (B) only, or the selection of both options (A andB). As a further example, in the cases of “A, B, and/or C” and “at leastone of A, B. and C”, such phrasing is intended to encompass theselection of the first listed option (A) only, or the selection of thesecond listed option (B) only, or the selection of the third listedoption (C) only, or the selection of the first and the second listedoptions (A and B) only, or the selection of the first and third listedoptions (A and C) only, or the selection of the second and third listedoptions (B and C) only, or the selection of all three options (A and Band C). This may be extended, as is clear to one of ordinary skill inthis and related arts, for as many items as are listed.

Also, as used herein, the word “signal” refers to, among other things,indicating something to a corresponding decoder. For example, in certainembodiments the encoder signals a particular one of a plurality ofparameters for deblocking filter in de-artifact filtering. In this way,in an embodiment the same parameter is used at both the encoder side andthe decoder side. Thus, for example, an encoder can transmit (explicitsignaling) a particular parameter to the decoder so that the decoder canuse the same particular parameter. Conversely, if the decoder alreadyhas the particular parameter as well as others, then signaling can beused without transmitting (implicit signaling) to simply allow thedecoder to know and select the particular parameter. By avoidingtransmission of any actual functions, a bit savings is realized invarious embodiments. It is to be appreciated that signaling can beaccomplished in a variety of ways. For example, one or more syntaxelements, flags, and so forth are used to signal information to acorresponding decoder in various embodiments. While the precedingrelates to the verb form of the word “signal”, the word “signal” canalso be used herein as a noun.

As will be evident to one of ordinary skill in the art, implementationscan produce a variety of signals formatted to carry information that canbe, for example, stored or transmitted. The information can include, forexample, instructions for performing a method, or data produced by oneof the described implementations. For example, a signal can be formattedto carry the bitstream of a described embodiment. Such a signal can beformatted, for example, as an electromagnetic wave (for example, using aradio frequency portion of spectrum) or as a baseband signal. Theformatting can include, for example, encoding a data stream andmodulating a carrier with the encoded data stream. The information thatthe signal carries can be, for example, analog or digital information.The signal can be transmitted over a variety of different wired orwireless links, as is known. The signal can be stored on aprocessor-readable medium.

We describe a number of embodiments. Features of these embodiments canbe provided alone or in any combination, across various claim categoriesand types. Further, embodiments can include one or more of the followingfeatures, devices, or aspects, alone or in any combination, acrossvarious claim categories and types:

-   -   Modifying the deblocking filter process applied in the decoder        and/or encoder,    -   Enabling several advanced deblocking filters in the decoder        and/or encoder,    -   Inserting in the signaling syntax elements that enable the        decoder to identify the deblocking filter process to use,    -   Selecting, based on these syntax elements, the deblocking filter        to apply at the decoder,    -   Adapting deblocking filter parameters in the decoder and/or        encoder,    -   Adapting the boundary strength of a deblocking filter in case        blocks at boundary are a combination of non-square or        non-rectangular blocks and/or the combination of unequal and/or        spatially variable weighting,    -   Adapting the filter strength of a deblocking filter in case        blocks at boundary are a combination of non-square or        non-rectangular blocks and/or the combination of unequal and/or        spatially variable weighting,    -   Determining a blending map for each sample of a block        representative of the weighted combination used in prediction of        each sample,    -   Adapting the boundary strength to the number of samples and/or        to the weight of samples used in bi-prediction,    -   Adapting the boundary strength to the relative weight of samples        used in combining inter and intra predicted samples or in        combining inter and inter predicted samples,    -   Adapting the boundary strength to the weight of samples used in        the prediction,    -   Normalizing the motion vectors using PDC difference of refence        frames for determining boundary strength,    -   Determining boundary strength comprises a test on whether the        prediction mode of one of the blocks at boundary is at least one        of MH, GBi or bi-prediction,    -   Modifying coding parameters and storing the modified parameters        for subsequent use in the deblocking filter (for instance in        determining of boundary strength parameters).    -   A bitstream or signal that includes one or more of the described        syntax elements, or variations thereof,    -   A bitstream or signal that includes syntax conveying information        generated according to any of the embodiments described,    -   Inserting in the signaling syntax elements that enable the        decoder to adapt deblocking filter in a manner corresponding to        that used by an encoder.    -   Creating and/or transmitting and/or receiving and/or decoding a        bitstream or signal that includes one or more of the described        syntax elements, or variations thereof,    -   Creating and/or transmitting and/or receiving and/or decoding        according to any of the embodiments described,    -   A method, process, apparatus, medium storing instructions,        medium storing data, or signal according to any of the        embodiments described,    -   A TV, set-top box, cell phone, tablet, or other electronic        device that performs adaptation of deblocking filter parameters        according to any of the embodiments described,    -   A TV, set-top box, cell phone, tablet, or other electronic        device that performs adaptation of deblocking filter parameters        according to any of the embodiments described, and that displays        (e.g. using a monitor, screen, or other type of display) a        resulting image,    -   A TV, set-top box, cell phone, tablet, or other electronic        device that selects (e.g. using a tuner) a channel to receive a        signal including an encoded image, and performs adaptation of        deblocking filter parameters according to any of the embodiments        described,    -   A TV, set-top box, cell phone, tablet, or other electronic        device that receives (e.g. using an antenna) a signal over the        air that includes an encoded image, and performs adaptation of        deblocking filter parameters according to any of the embodiments        described.

1-16. (canceled)
 17. A method comprising: decoding a part of an image;determining at least one boundary between a first block of samples and asecond block of samples, the first block and second block belonging tothe decoded image part; determining a boundary strength of a deblockingfiltering based on at least a prediction mode of the first block; andfiltering samples of the first block and of the second block based onthe boundary strength; wherein when the first block of samples belongsto a geometric partitioning mode inter block resulting from a weightedcombination of a first predictor and a second predictor, the predictionmode of the first block used in the determining of the boundary strengthis one of an inter bi-directional prediction mode or an interuni-directional prediction mode and the prediction mode of the firstblock used in the determining of the boundary strength is correlatedwith a weight associated with at least a sample in the first predictoror with a weight associated with at least a sample in the secondpredictor.
 18. The method of claim 17, wherein the prediction mode ofthe first block used in the determining of the boundary strength is aninter bi-directional prediction mode in case the weight of a sample inthe first predictor is above a level and the weight of a sample in thesecond predictor is above a level.
 19. The method of claim 17, whereinthe prediction mode of the first block used in the determining of theboundary strength is an inter uni-directional prediction mode in casethe weight of a sample in the first predictor is equal to or less than alevel or the weight of a sample in the second predictor is equal to orless than a level.
 20. The method of claim 17, wherein prediction modeof the first block used in the determining of the boundary strength isan inter bi-directional prediction mode in case a number of samples inthe first predictor having a weight above a level is higher than asample amount and a number of samples in the second predictor having aweight above the level is higher than the sample amount.
 21. The methodof claim 17, wherein prediction mode of the first block used in thedetermining of the boundary strength is an inter uni-directionalprediction mode in case a number of samples in the first predictorhaving a weight above a level is lower or equal than a sample amount orin case a number of samples in the second predictor having a weightabove a level is lower or equal than the sample amount.
 22. The methodof claim 17, wherein the weight of a sample in the first predictor isequal to or less than a level or the weight of a sample in the secondpredictor is equal to or less than a level, and wherein the level is setto zero.
 23. The method of claim 17, wherein the greater a distance ofthe sample with an edge of the geometric partitioning mode inter block,the smaller the weight associated with the at least a sample in thefirst predictor or the smaller the weight associated with the at least asample in the second predictor.
 24. The method of claim 17, wherein thefirst block of samples and a second block of samples are 4×4 sizedblocks.
 25. An apparatus comprising: at least one processor configuredto: decode a part of an image; determine that at least one boundarybetween a first block of samples and a second block of samples, thefirst block and second block belonging to the decoded image part;determine a boundary strength of a deblocking filter based on at least aprediction mode of the first block; and apply the deblocking filter tosamples of the first block and of the second block based on the boundarystrength; wherein when the first block of samples belongs to a geometricpartitioning mode inter block resulting from a weighted combination of afirst predictor and a second predictor, the prediction mode of the firstblock used to determine the boundary strength is one of an interbi-directional prediction mode or an inter uni-directional predictionmode and the prediction mode of the first block used to determine theboundary strength is correlated with a weight associated with at least asample in the first predictor or with a weight associated with at leasta sample in the second predictor.
 26. The apparatus of claim 25, whereinthe prediction mode of the first block used to determine the boundarystrength is an inter bi-directional prediction mode in case the weightof a sample in the first predictor is above a level and the weight of asample in the second predictor is above a level.
 27. The apparatus ofclaim 25, wherein the prediction mode of the first block used todetermine the boundary strength is an inter uni-directional predictionmode in case the weight of a sample in the first predictor is equal toor less than a level or the weight of a sample in the second predictoris equal to or less than a level.
 28. The apparatus of claim 25, whereinprediction mode of the first block used to determine the boundarystrength is an inter bi-directional prediction mode in case a number ofsamples in the first predictor having a weight above a level is higherthan a sample amount and a number of samples in the second predictorhaving a weight above the level is higher than the sample amount. 29.The apparatus of claim 25, wherein prediction mode of the first blockused to determine the boundary strength is an inter uni-directionalprediction mode in case a number of samples in the first predictorhaving a weight above a level is lower or equal than a sample amount orin case a number of samples in the second predictor having a weightabove a level is lower or equal than the sample amount.
 30. Theapparatus of claim 25, wherein the weight of a sample in the firstpredictor is equal to or less than a level or the weight of a sample inthe second predictor is equal to or less than a level, and wherein thelevel is set to zero.
 31. The apparatus of claim 25, wherein the greatera distance of the sample with an edge of the geometric partitioning modeinter block, the smaller the weight associated with the at least asample in the first predictor or the smaller the weight associated withthe at least a sample in the second predictor.
 32. The apparatus ofclaim 25, wherein the first block of samples and a second block ofsamples are 4×4 sized blocks.
 33. A method of encoding an image,comprising: reconstructing a part of the image; determining at least oneboundary between a first block of samples and a second block of samples,the first block and second block belonging to the reconstructed imagepart; determining a boundary strength of a deblocking filtering based onat least a prediction mode of the first block; and filtering samples ofthe first block and of the second block based on the boundary strength;wherein when the first block of samples belongs to a geometricpartitioning mode inter block resulting from a weighted combination of afirst predictor and a second predictor, the prediction mode of the firstblock used in the determining of the boundary strength is one of aninter bi-directional prediction mode or an inter uni-directionalprediction mode and the prediction mode of the first block used in thedetermining of the boundary strength is correlated with a weightassociated with at least a sample in the first predictor or with aweight associated with at least a sample in the second predictor. 34.The method of claim 33, wherein the prediction mode of the first blockused in the determining of the boundary strength is an interbi-directional prediction mode in case the weight of a sample in thefirst predictor is above a level and the weight of a sample in thesecond predictor is above a level.
 35. The method of claim 33, whereinthe prediction mode of the first block used in the determining of theboundary strength is an inter uni-directional prediction mode in casethe weight of a sample in the first predictor is equal to or less than alevel or the weight of a sample in the second predictor is equal to orless than a level.
 36. An apparatus comprising: at least one processorto encode an image, configured to: reconstruct a part of the image;determine that at least one boundary between a first block of samplesand a second block of samples, the first block and second blockbelonging to the reconstructed image part; determine a boundary strengthof a deblocking filter based on at least a prediction mode of the firstblock; and apply the deblocking filter to samples of the first block andof the second block based on the boundary strength; wherein when thefirst block of samples belongs to a geometric partitioning mode interblock resulting from a weighted combination of a first predictor and asecond predictor, the prediction mode of the first block used todetermine the boundary strength is one of an inter bi-directionalprediction mode or an inter uni-directional prediction mode and theprediction mode of the first block used to determine the boundarystrength is correlated with a weight associated with at least a samplein the first predictor or with a weight associated with at least asample in the second predictor.
 37. The apparatus of claim 36, whereinthe prediction mode of the first block used to determine the boundarystrength is an inter bi-directional prediction mode in case the weightof a sample in the first predictor is above a level and the weight of asample in the second predictor is above a level.
 38. The apparatus ofclaim 36, wherein the prediction mode of the first block used todetermine the boundary strength is an inter uni-directional predictionmode in case the weight of a sample in the first predictor is equal toor less than a level or the weight of a sample in the second predictoris equal to or less than a level.